| Course title | Advanced Remote Sensing |
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| Course code | KGI/XSARS |
| Organizational form of instruction | Lecture + Exercise |
| Level of course | unspecified |
| Year of study | not specified |
| Semester | Winter |
| Number of ECTS credits | 6 |
| Language of instruction | English |
| Status of course | unspecified |
| Form of instruction | Face-to-face |
| Work placements | This is not an internship |
| Recommended optional programme components | None |
| Lecturer(s) |
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| Course content |
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This introductory seminar course advances both depth and extent of skills in automated image analysis of remotely sensed data. This course covers the full workflow from image acquisition (new sensor types and devices), over advanced pre-processing and pre-classification techniques, and object-based image understanding including quality assessment. The schedule includes the following topics: - Space, EO applications, Copernicus - Spatial concepts in image analysis - Hyperspectral remote sensing - principles - Radio detection and ranging (RaDAR) - techniques and applications - Hyperspatial remote sensing (RPAS) - techniques and applications - Light detection and ranging (LiDAR) - techniques and applications - Radiometric correction - Image segmentation - Image convolution - Filters / CNN - Knowledge representation - Knowledge-based classification - Advanced statistical classifiers (SVM, random forest) - Class modelling - Quality assessment and validation The single topics will be deepened by hands-on exercises and assignments using relevant software packages.
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| Learning activities and teaching methods |
| unspecified |
| Learning outcomes |
| Prerequisites |
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unspecified
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| Assessment methods and criteria |
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unspecified
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| Recommended literature |
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| Study plans that include the course |
| Faculty | Study plan (Version) | Category of Branch/Specialization | Recommended semester |
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